How do AI models learn and adapt to new data?

AI models learn and adapt to new data like a child learning new words by hearing them again and again.

Imagine you have a friend who is really good at guessing what you're thinking. At first, they only know a few words, so they make guesses based on the simple things you say. But every time you talk to them, they get better at understanding you, because they remember how your sentences sounded before, and they use that to figure out what you might be saying now.

AI models are like that friend. When they start learning, they have a basic idea of how things work. They look at examples, like words in a sentence or numbers in a math problem, and try to find patterns. Each time they see new data, they compare it with what they already know and adjust their thinking.

When AI models learn from new data, it's like getting extra practice. They look at the new examples, think about how they differ from the old ones, and update their understanding. It’s like when you learn to ride a bike, at first, you wobble a lot, but with each try, you get more steady.

So AI models keep improving, just like you do when you practice something every day!